ANALYSIS OF IMAGE RECOGNITION METHODS AND THEIR CLASSIFICATION

In the context of the Russian-Ukrainian war, new challenges arise for electronic intelligence. The radio frequency spectrum is saturated with various types of signals, and modern communications have a high level of security. An important stage of signal processing at electronic intelligence posts is their recognition. Most weapons automatically recognize signals by measuring their input parameters, however, due to the low signal-to-noise ratio, this process can be difficult. Nevertheless, almost all modern electronic intelligence equipment displays spectrograms on which the signal can be clearly recognized by human vision. Given the widespread use of image recognition technologies in various industries, it is important to consider the methods and techniques of this process and explore the possibility of using them to solve the problem of signal recognition. The article discusses the concept of artificial intelligence with a special emphasis on the role of computer vision in this field. A classification of image recognition methods is carried out according to the scheme developed on the basis of approaches. In addition, the main stages of computer vision are analyzed, including their functional components and content. Particular attention is paid to the methods of pattern recognition, in particular to the three main types of these methods. The three main types of image recognition methods are distinguished, and their advantages and disadvantages are analyzed. The article also provides practical examples of the implementation of these methods. The final stage of the study was the selection of a method for further experimental and theoretical research.